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Mathematical modeling of the optimal management of participation in energy markets of an aggregate of distributed flexibility resources in the Italian context and case study applications

reports - Deliverable

Mathematical modeling of the optimal management of participation in energy markets of an aggregate of distributed flexibility resources in the Italian context and case study applications

In this paper, we present two mathematical models developed to determine the supply curve in the dispatching services market and to manage energy exchanges of distributed resources. The first model is based on a hierarchical optimization method. The second is based on a stochastic approach applied to a moving window.

The process of decarbonizing the energy sector calls for the expansion of entities qualified to provide ancillary services traditionally provided by fossil-fueled large-scale generation. To this end, in 2017, the The Italian Regulatory Authority for Energy, Networks and Environment (ARERA) issued Resolution 300/2017/R/eel, which promotes experimentation with the provision of certain ancillary services by distributed resource aggregators. For this reason, it is interesting to simulate the techno-economic feasibility of providing ancillary services by these new market entrants.

 

In this paper, two models are proposed that allow, first, to identify the supply curves of an aggregate of distributed resources in the dispatching services market and, second, to control, in real time, the flexible resources within the aggregate.

 

The first model is based on the two-level hierarchical optimization method. The first level makes it possible to determine the status of flexible resources at the opening of the market for dispatching services. The second level is based on an iteratively solved mixed-integer optimization model; it allows determining the marginal costs of providing ancillary services to the grid, based on which, the model defines a supply curve in the dispatch services market. This curve is composed of 3 or 4 steps, each of which is characterized by a price-quantity pair.

 

The second proposed model allows real-time management of flexible resources within the aggregate in order to meet the schedules defined by the markets and to ensure compliance with the comfort constraints of aggregate users. This second model is based on a stochastic optimization algorithm applied to a moving time window: the peculiarity of this approach lies in the possibility of real-time management of flexible resources considering the forecasts of energy exchanges in subsequent instants and the corresponding uncertainties.

 

Finally, the preliminary results obtained are reported and commented on, which show that an aggregate composed of about 2,500 residential prosumers is able to offer 3 MW of flexibility to the electric system without affecting the comfort level of users.

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